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<div class="title">decision_tree_trainer.h</div>  </div>
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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/*</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Software License Agreement (BSD License)</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> *  Point Cloud Library (PCL) - www.pointclouds.org</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> *  Copyright (c) 2010-2011, Willow Garage, Inc.</span></div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment"> *  All rights reserved.</span></div>
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<div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="comment"> *  Redistribution and use in source and binary forms, with or without</span></div>
<div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="comment"> *  modification, are permitted provided that the following conditions</span></div>
<div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="comment"> *  are met:</span></div>
<div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="comment"> *   * Redistributions of source code must retain the above copyright</span></div>
<div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="comment"> *     notice, this list of conditions and the following disclaimer.</span></div>
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<div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;<span class="comment"> */</span></div>
<div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;  </div>
<div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;<span class="preprocessor">#ifndef PCL_ML_DT_DECISION_TREE_TRAINER_H_</span></div>
<div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;<span class="preprocessor">#define PCL_ML_DT_DECISION_TREE_TRAINER_H_</span></div>
<div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160; </div>
<div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="common_2include_2pcl_2common_2common_8h.html">pcl/common/common.h</a>&gt;</span></div>
<div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160; </div>
<div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;<span class="preprocessor">#include &lt;pcl/ml/dt/decision_tree.h&gt;</span></div>
<div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;<span class="preprocessor">#include &lt;pcl/ml/feature_handler.h&gt;</span></div>
<div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;<span class="preprocessor">#include &lt;pcl/ml/stats_estimator.h&gt;</span></div>
<div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;<span class="preprocessor">#include &lt;pcl/ml/dt/decision_tree_data_provider.h&gt;</span></div>
<div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160; </div>
<div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;<span class="preprocessor">#include &lt;vector&gt;</span></div>
<div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160; </div>
<div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;<span class="keyword">namespace </span>pcl</div>
<div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;{</div>
<div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160; </div>
<div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;  <span class="keyword">template</span> &lt;</div>
<div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;    <span class="keyword">class </span>FeatureType,</div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;    <span class="keyword">class </span>DataSet,</div>
<div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;    <span class="keyword">class </span>LabelType,</div>
<div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;    <span class="keyword">class </span>ExampleIndex,</div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;    <span class="keyword">class </span>NodeType &gt;</div>
<div class="line"><a name="l00060"></a><span class="lineno"><a class="line" href="classpcl_1_1_decision_tree_trainer.html">   60</a></span>&#160;  <span class="keyword">class </span>PCL_EXPORTS <a class="code" href="classpcl_1_1_decision_tree_trainer.html">DecisionTreeTrainer</a></div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;  {</div>
<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;  </div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;    <span class="keyword">public</span>:</div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160; </div>
<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;      <a class="code" href="classpcl_1_1_decision_tree_trainer.html">DecisionTreeTrainer</a> ();</div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;      <span class="keyword">virtual</span> </div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;      ~<a class="code" href="classpcl_1_1_decision_tree_trainer.html">DecisionTreeTrainer</a> ();</div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160; </div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;      <span class="keyword">inline</span> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00075"></a><span class="lineno"><a class="line" href="classpcl_1_1_decision_tree_trainer.html#a92e70dbf0182027f707a137d3a9bf4bb">   75</a></span>&#160;      <a class="code" href="classpcl_1_1_decision_tree_trainer.html#a92e70dbf0182027f707a137d3a9bf4bb">setFeatureHandler</a> (<a class="code" href="classpcl_1_1_feature_handler.html">pcl::FeatureHandler&lt;FeatureType, DataSet, ExampleIndex&gt;</a> &amp; feature_handler)</div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;      {</div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;        feature_handler_ = &amp;feature_handler;</div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;      }</div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160; </div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;      <span class="keyword">inline</span> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00084"></a><span class="lineno"><a class="line" href="classpcl_1_1_decision_tree_trainer.html#a4e8c427ba5b8efa0df8464eb5e7258a2">   84</a></span>&#160;      <a class="code" href="classpcl_1_1_decision_tree_trainer.html#a4e8c427ba5b8efa0df8464eb5e7258a2">setStatsEstimator</a> (<a class="code" href="classpcl_1_1_stats_estimator.html">pcl::StatsEstimator&lt;LabelType, NodeType, DataSet, ExampleIndex&gt;</a> &amp; stats_estimator)</div>
<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;      {</div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;        stats_estimator_ = &amp;stats_estimator;</div>
<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;      }</div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160; </div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;      <span class="keyword">inline</span> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00093"></a><span class="lineno"><a class="line" href="classpcl_1_1_decision_tree_trainer.html#a90f7f50df5c6d7ccc58b6def6430e3a9">   93</a></span>&#160;      <a class="code" href="classpcl_1_1_decision_tree_trainer.html#a90f7f50df5c6d7ccc58b6def6430e3a9">setMaxTreeDepth</a> (<span class="keyword">const</span> <span class="keywordtype">size_t</span> max_tree_depth)</div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;      {</div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;        max_tree_depth_ = max_tree_depth;</div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;      }</div>
<div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160; </div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;      <span class="keyword">inline</span> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00102"></a><span class="lineno"><a class="line" href="classpcl_1_1_decision_tree_trainer.html#a31b6a9b0ec5b627cf621776b63f70be7">  102</a></span>&#160;      <a class="code" href="classpcl_1_1_decision_tree_trainer.html#a31b6a9b0ec5b627cf621776b63f70be7">setNumOfFeatures</a> (<span class="keyword">const</span> <span class="keywordtype">size_t</span> num_of_features)</div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;      {</div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;        num_of_features_ = num_of_features;</div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;      }</div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160; </div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;      <span class="keyword">inline</span> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00111"></a><span class="lineno"><a class="line" href="classpcl_1_1_decision_tree_trainer.html#a47658b78a12f0f8dc1acb6f9974c7ec3">  111</a></span>&#160;      <a class="code" href="classpcl_1_1_decision_tree_trainer.html#a47658b78a12f0f8dc1acb6f9974c7ec3">setNumOfThresholds</a> (<span class="keyword">const</span> <span class="keywordtype">size_t</span> num_of_threshold)</div>
<div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;      {</div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;        num_of_thresholds_ = num_of_threshold;</div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;      }</div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160; </div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;      <span class="keyword">inline</span> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00120"></a><span class="lineno"><a class="line" href="classpcl_1_1_decision_tree_trainer.html#aa84e9a077ade50a8f246c2d5c8ebb72e">  120</a></span>&#160;      <a class="code" href="classpcl_1_1_decision_tree_trainer.html#aa84e9a077ade50a8f246c2d5c8ebb72e">setTrainingDataSet</a> (DataSet &amp; data_set)</div>
<div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;      {</div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;        data_set_ = data_set;</div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;      }</div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160; </div>
<div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;      <span class="keyword">inline</span> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00129"></a><span class="lineno"><a class="line" href="classpcl_1_1_decision_tree_trainer.html#adfa12496668f181e8128e657fdb0bb01">  129</a></span>&#160;      <a class="code" href="classpcl_1_1_decision_tree_trainer.html#adfa12496668f181e8128e657fdb0bb01">setExamples</a> (std::vector&lt;ExampleIndex&gt; &amp; examples)</div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;      {</div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;        examples_ = examples;</div>
<div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;      }</div>
<div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160; </div>
<div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;      <span class="keyword">inline</span> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00138"></a><span class="lineno"><a class="line" href="classpcl_1_1_decision_tree_trainer.html#add4301c8ebb4704365ca7e6c5293a7ff">  138</a></span>&#160;      <a class="code" href="classpcl_1_1_decision_tree_trainer.html#add4301c8ebb4704365ca7e6c5293a7ff">setLabelData</a> (std::vector&lt;LabelType&gt; &amp; label_data)</div>
<div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;      {</div>
<div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;        label_data_ = label_data;</div>
<div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;      }</div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160; </div>
<div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;      <span class="keyword">inline</span> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00147"></a><span class="lineno"><a class="line" href="classpcl_1_1_decision_tree_trainer.html#ae827187aa26efc229653ef2eda9153b4">  147</a></span>&#160;      <a class="code" href="classpcl_1_1_decision_tree_trainer.html#ae827187aa26efc229653ef2eda9153b4">setMinExamplesForSplit</a> (<span class="keywordtype">size_t</span> n)</div>
<div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;      {</div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;        min_examples_for_split_ = n;</div>
<div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;      }</div>
<div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160; </div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;      <span class="keywordtype">void</span></div>
<div class="line"><a name="l00156"></a><span class="lineno"><a class="line" href="classpcl_1_1_decision_tree_trainer.html#acf9dfd53b3ee6f9da23b608097ff9127">  156</a></span>&#160;      <a class="code" href="classpcl_1_1_decision_tree_trainer.html#acf9dfd53b3ee6f9da23b608097ff9127">setThresholds</a> (std::vector&lt;float&gt; &amp; thres)</div>
<div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;      {</div>
<div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;        thresholds_ = thres;</div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;      }</div>
<div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160; </div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;      <span class="keywordtype">void</span></div>
<div class="line"><a name="l00165"></a><span class="lineno"><a class="line" href="classpcl_1_1_decision_tree_trainer.html#a60ffc9a571d7fa634dfdbb340e451c20">  165</a></span>&#160;      <a class="code" href="classpcl_1_1_decision_tree_trainer.html#a60ffc9a571d7fa634dfdbb340e451c20">setDecisionTreeDataProvider</a> (boost::shared_ptr&lt;<a class="code" href="classpcl_1_1_decision_tree_trainer_data_provider.html">pcl::DecisionTreeTrainerDataProvider&lt;FeatureType, DataSet, LabelType, ExampleIndex, NodeType&gt;</a> &gt; &amp; dtdp)</div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;      {</div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;        decision_tree_trainer_data_provider_ = dtdp;</div>
<div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;      }</div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160; </div>
<div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;      <span class="keywordtype">void</span></div>
<div class="line"><a name="l00174"></a><span class="lineno"><a class="line" href="classpcl_1_1_decision_tree_trainer.html#a2038658c7d8bb5b237aab6b3047c607f">  174</a></span>&#160;      <a class="code" href="classpcl_1_1_decision_tree_trainer.html#a2038658c7d8bb5b237aab6b3047c607f">setRandomFeaturesAtSplitNode</a> (<span class="keywordtype">bool</span> b)</div>
<div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;      {</div>
<div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;        random_features_at_split_node_ = b;</div>
<div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;      }</div>
<div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160; </div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;      <span class="keywordtype">void</span></div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;      train (<a class="code" href="classpcl_1_1_decision_tree.html">DecisionTree&lt;NodeType&gt;</a> &amp; tree);</div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160; </div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;    <span class="keyword">protected</span>:</div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160; </div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;      <span class="keywordtype">void</span></div>
<div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;      trainDecisionTreeNode (std::vector&lt;FeatureType&gt; &amp; features,</div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;                             std::vector&lt;ExampleIndex&gt; &amp; examples,</div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;                             std::vector&lt;LabelType&gt; &amp; label_data,</div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;                             <span class="keywordtype">size_t</span> max_depth,</div>
<div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;                             NodeType &amp; node);</div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160; </div>
<div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;      <span class="keyword">static</span> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;      createThresholdsUniform (<span class="keyword">const</span> <span class="keywordtype">size_t</span> num_of_thresholds,</div>
<div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;                               std::vector&lt;float&gt; &amp; values,</div>
<div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;                               std::vector&lt;float&gt; &amp; thresholds);</div>
<div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160; </div>
<div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;    <span class="keyword">private</span>:</div>
<div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160; </div>
<div class="line"><a name="l00214"></a><span class="lineno"><a class="line" href="classpcl_1_1_decision_tree_trainer.html#ae52d59ebb69707299a041792b22f6c27">  214</a></span>&#160;      <span class="keywordtype">size_t</span> <a class="code" href="classpcl_1_1_decision_tree_trainer.html#ae52d59ebb69707299a041792b22f6c27">max_tree_depth_</a>;</div>
<div class="line"><a name="l00216"></a><span class="lineno"><a class="line" href="classpcl_1_1_decision_tree_trainer.html#a5b7857d6fcd89d964fa1b2ba07964ac0">  216</a></span>&#160;      <span class="keywordtype">size_t</span> <a class="code" href="classpcl_1_1_decision_tree_trainer.html#a5b7857d6fcd89d964fa1b2ba07964ac0">num_of_features_</a>;</div>
<div class="line"><a name="l00218"></a><span class="lineno"><a class="line" href="classpcl_1_1_decision_tree_trainer.html#a30525d111a074464d9631b0ba900514f">  218</a></span>&#160;      <span class="keywordtype">size_t</span> <a class="code" href="classpcl_1_1_decision_tree_trainer.html#a30525d111a074464d9631b0ba900514f">num_of_thresholds_</a>;</div>
<div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160; </div>
<div class="line"><a name="l00221"></a><span class="lineno"><a class="line" href="classpcl_1_1_decision_tree_trainer.html#afca25306578c18cc5e6891d1fde37370">  221</a></span>&#160;      <a class="code" href="classpcl_1_1_feature_handler.html">pcl::FeatureHandler&lt;FeatureType, DataSet, ExampleIndex&gt;</a> * <a class="code" href="classpcl_1_1_decision_tree_trainer.html#afca25306578c18cc5e6891d1fde37370">feature_handler_</a>;</div>
<div class="line"><a name="l00223"></a><span class="lineno"><a class="line" href="classpcl_1_1_decision_tree_trainer.html#a02407f5bbd2950a55546f502a5773043">  223</a></span>&#160;      <a class="code" href="classpcl_1_1_stats_estimator.html">pcl::StatsEstimator&lt;LabelType, NodeType, DataSet, ExampleIndex&gt;</a> * <a class="code" href="classpcl_1_1_decision_tree_trainer.html#a02407f5bbd2950a55546f502a5773043">stats_estimator_</a>;</div>
<div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160; </div>
<div class="line"><a name="l00226"></a><span class="lineno"><a class="line" href="classpcl_1_1_decision_tree_trainer.html#a7fa0c3d3f6f233e3dc0ec6db86fadd18">  226</a></span>&#160;      DataSet <a class="code" href="classpcl_1_1_decision_tree_trainer.html#a7fa0c3d3f6f233e3dc0ec6db86fadd18">data_set_</a>;</div>
<div class="line"><a name="l00228"></a><span class="lineno"><a class="line" href="classpcl_1_1_decision_tree_trainer.html#a566006e8f96c21cd21b5030bfebdf77e">  228</a></span>&#160;      std::vector&lt;LabelType&gt; <a class="code" href="classpcl_1_1_decision_tree_trainer.html#a566006e8f96c21cd21b5030bfebdf77e">label_data_</a>;</div>
<div class="line"><a name="l00230"></a><span class="lineno"><a class="line" href="classpcl_1_1_decision_tree_trainer.html#a377137a6d21e986ab79802cd8d2d35e5">  230</a></span>&#160;      std::vector&lt;ExampleIndex&gt; <a class="code" href="classpcl_1_1_decision_tree_trainer.html#a377137a6d21e986ab79802cd8d2d35e5">examples_</a>;</div>
<div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;  </div>
<div class="line"><a name="l00233"></a><span class="lineno"><a class="line" href="classpcl_1_1_decision_tree_trainer.html#abf5484a41b853b82f4e5399c7cd28127">  233</a></span>&#160;      <span class="keywordtype">size_t</span> <a class="code" href="classpcl_1_1_decision_tree_trainer.html#abf5484a41b853b82f4e5399c7cd28127">min_examples_for_split_</a>;</div>
<div class="line"><a name="l00235"></a><span class="lineno"><a class="line" href="classpcl_1_1_decision_tree_trainer.html#ad3d53bab672146cea68fd91e86a169fc">  235</a></span>&#160;      std::vector&lt;float&gt; <a class="code" href="classpcl_1_1_decision_tree_trainer.html#ad3d53bab672146cea68fd91e86a169fc">thresholds_</a>;</div>
<div class="line"><a name="l00237"></a><span class="lineno"><a class="line" href="classpcl_1_1_decision_tree_trainer.html#a29fd755841928ef5342dbf19e01ae028">  237</a></span>&#160;      boost::shared_ptr&lt;pcl::DecisionTreeTrainerDataProvider&lt;FeatureType, DataSet, LabelType, ExampleIndex, NodeType&gt; &gt; <a class="code" href="classpcl_1_1_decision_tree_trainer.html#a29fd755841928ef5342dbf19e01ae028">decision_tree_trainer_data_provider_</a>;</div>
<div class="line"><a name="l00239"></a><span class="lineno"><a class="line" href="classpcl_1_1_decision_tree_trainer.html#a463ddc17542e98ef217d1454ac3250ae">  239</a></span>&#160;      <span class="keywordtype">bool</span> <a class="code" href="classpcl_1_1_decision_tree_trainer.html#a463ddc17542e98ef217d1454ac3250ae">random_features_at_split_node_</a>;</div>
<div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;  };</div>
<div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160; </div>
<div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;}</div>
<div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160; </div>
<div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;<span class="preprocessor">#include &lt;pcl/ml/impl/dt/decision_tree_trainer.hpp&gt;</span></div>
<div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160; </div>
<div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_html"><div class="ttname"><a href="classpcl_1_1_decision_tree.html">pcl::DecisionTree</a></div><div class="ttdoc">Class representing a decision tree.</div><div class="ttdef"><b>Definition:</b> decision_tree.h:52</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_data_provider_html"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer_data_provider.html">pcl::DecisionTreeTrainerDataProvider</a></div><div class="ttdef"><b>Definition:</b> decision_tree_data_provider.h:47</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_html"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer.html">pcl::DecisionTreeTrainer</a></div><div class="ttdoc">Trainer for decision trees.</div><div class="ttdef"><b>Definition:</b> decision_tree_trainer.h:61</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_html_a02407f5bbd2950a55546f502a5773043"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer.html#a02407f5bbd2950a55546f502a5773043">pcl::DecisionTreeTrainer::stats_estimator_</a></div><div class="ttdeci">pcl::StatsEstimator&lt; LabelType, NodeType, DataSet, ExampleIndex &gt; * stats_estimator_</div><div class="ttdoc">StatsEstimator instance, responsible for gathering stats about a node.</div><div class="ttdef"><b>Definition:</b> decision_tree_trainer.h:223</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_html_a2038658c7d8bb5b237aab6b3047c607f"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer.html#a2038658c7d8bb5b237aab6b3047c607f">pcl::DecisionTreeTrainer::setRandomFeaturesAtSplitNode</a></div><div class="ttdeci">void setRandomFeaturesAtSplitNode(bool b)</div><div class="ttdoc">Specify if the features are randomly generated at each split node.</div><div class="ttdef"><b>Definition:</b> decision_tree_trainer.h:174</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_html_a29fd755841928ef5342dbf19e01ae028"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer.html#a29fd755841928ef5342dbf19e01ae028">pcl::DecisionTreeTrainer::decision_tree_trainer_data_provider_</a></div><div class="ttdeci">boost::shared_ptr&lt; pcl::DecisionTreeTrainerDataProvider&lt; FeatureType, DataSet, LabelType, ExampleIndex, NodeType &gt; &gt; decision_tree_trainer_data_provider_</div><div class="ttdoc">The data provider which is called before training a specific tree, if pointer is NULL,...</div><div class="ttdef"><b>Definition:</b> decision_tree_trainer.h:237</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_html_a30525d111a074464d9631b0ba900514f"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer.html#a30525d111a074464d9631b0ba900514f">pcl::DecisionTreeTrainer::num_of_thresholds_</a></div><div class="ttdeci">size_t num_of_thresholds_</div><div class="ttdoc">Number of thresholds.</div><div class="ttdef"><b>Definition:</b> decision_tree_trainer.h:218</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_html_a31b6a9b0ec5b627cf621776b63f70be7"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer.html#a31b6a9b0ec5b627cf621776b63f70be7">pcl::DecisionTreeTrainer::setNumOfFeatures</a></div><div class="ttdeci">void setNumOfFeatures(const size_t num_of_features)</div><div class="ttdoc">Sets the number of features used to find optimal decision features.</div><div class="ttdef"><b>Definition:</b> decision_tree_trainer.h:102</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_html_a377137a6d21e986ab79802cd8d2d35e5"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer.html#a377137a6d21e986ab79802cd8d2d35e5">pcl::DecisionTreeTrainer::examples_</a></div><div class="ttdeci">std::vector&lt; ExampleIndex &gt; examples_</div><div class="ttdoc">The example data.</div><div class="ttdef"><b>Definition:</b> decision_tree_trainer.h:230</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_html_a463ddc17542e98ef217d1454ac3250ae"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer.html#a463ddc17542e98ef217d1454ac3250ae">pcl::DecisionTreeTrainer::random_features_at_split_node_</a></div><div class="ttdeci">bool random_features_at_split_node_</div><div class="ttdoc">If true, random features are generated at each node, otherwise, at start of training the tree</div><div class="ttdef"><b>Definition:</b> decision_tree_trainer.h:239</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_html_a47658b78a12f0f8dc1acb6f9974c7ec3"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer.html#a47658b78a12f0f8dc1acb6f9974c7ec3">pcl::DecisionTreeTrainer::setNumOfThresholds</a></div><div class="ttdeci">void setNumOfThresholds(const size_t num_of_threshold)</div><div class="ttdoc">Sets the number of thresholds tested for finding the optimal decision threshold on the feature respon...</div><div class="ttdef"><b>Definition:</b> decision_tree_trainer.h:111</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_html_a4e8c427ba5b8efa0df8464eb5e7258a2"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer.html#a4e8c427ba5b8efa0df8464eb5e7258a2">pcl::DecisionTreeTrainer::setStatsEstimator</a></div><div class="ttdeci">void setStatsEstimator(pcl::StatsEstimator&lt; LabelType, NodeType, DataSet, ExampleIndex &gt; &amp;stats_estimator)</div><div class="ttdoc">Sets the object for estimating the statistics for tree nodes.</div><div class="ttdef"><b>Definition:</b> decision_tree_trainer.h:84</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_html_a566006e8f96c21cd21b5030bfebdf77e"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer.html#a566006e8f96c21cd21b5030bfebdf77e">pcl::DecisionTreeTrainer::label_data_</a></div><div class="ttdeci">std::vector&lt; LabelType &gt; label_data_</div><div class="ttdoc">The label data.</div><div class="ttdef"><b>Definition:</b> decision_tree_trainer.h:228</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_html_a5b7857d6fcd89d964fa1b2ba07964ac0"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer.html#a5b7857d6fcd89d964fa1b2ba07964ac0">pcl::DecisionTreeTrainer::num_of_features_</a></div><div class="ttdeci">size_t num_of_features_</div><div class="ttdoc">Number of features used to find optimal decision features.</div><div class="ttdef"><b>Definition:</b> decision_tree_trainer.h:216</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_html_a60ffc9a571d7fa634dfdbb340e451c20"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer.html#a60ffc9a571d7fa634dfdbb340e451c20">pcl::DecisionTreeTrainer::setDecisionTreeDataProvider</a></div><div class="ttdeci">void setDecisionTreeDataProvider(boost::shared_ptr&lt; pcl::DecisionTreeTrainerDataProvider&lt; FeatureType, DataSet, LabelType, ExampleIndex, NodeType &gt; &gt; &amp;dtdp)</div><div class="ttdoc">Specify the data provider.</div><div class="ttdef"><b>Definition:</b> decision_tree_trainer.h:165</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_html_a7fa0c3d3f6f233e3dc0ec6db86fadd18"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer.html#a7fa0c3d3f6f233e3dc0ec6db86fadd18">pcl::DecisionTreeTrainer::data_set_</a></div><div class="ttdeci">DataSet data_set_</div><div class="ttdoc">The training data set.</div><div class="ttdef"><b>Definition:</b> decision_tree_trainer.h:226</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_html_a90f7f50df5c6d7ccc58b6def6430e3a9"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer.html#a90f7f50df5c6d7ccc58b6def6430e3a9">pcl::DecisionTreeTrainer::setMaxTreeDepth</a></div><div class="ttdeci">void setMaxTreeDepth(const size_t max_tree_depth)</div><div class="ttdoc">Sets the maximum depth of the learned tree.</div><div class="ttdef"><b>Definition:</b> decision_tree_trainer.h:93</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_html_a92e70dbf0182027f707a137d3a9bf4bb"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer.html#a92e70dbf0182027f707a137d3a9bf4bb">pcl::DecisionTreeTrainer::setFeatureHandler</a></div><div class="ttdeci">void setFeatureHandler(pcl::FeatureHandler&lt; FeatureType, DataSet, ExampleIndex &gt; &amp;feature_handler)</div><div class="ttdoc">Sets the feature handler used to create and evaluate features.</div><div class="ttdef"><b>Definition:</b> decision_tree_trainer.h:75</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_html_aa84e9a077ade50a8f246c2d5c8ebb72e"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer.html#aa84e9a077ade50a8f246c2d5c8ebb72e">pcl::DecisionTreeTrainer::setTrainingDataSet</a></div><div class="ttdeci">void setTrainingDataSet(DataSet &amp;data_set)</div><div class="ttdoc">Sets the input data set used for training.</div><div class="ttdef"><b>Definition:</b> decision_tree_trainer.h:120</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_html_abf5484a41b853b82f4e5399c7cd28127"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer.html#abf5484a41b853b82f4e5399c7cd28127">pcl::DecisionTreeTrainer::min_examples_for_split_</a></div><div class="ttdeci">size_t min_examples_for_split_</div><div class="ttdoc">Minimum number of examples to split a node.</div><div class="ttdef"><b>Definition:</b> decision_tree_trainer.h:233</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_html_acf9dfd53b3ee6f9da23b608097ff9127"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer.html#acf9dfd53b3ee6f9da23b608097ff9127">pcl::DecisionTreeTrainer::setThresholds</a></div><div class="ttdeci">void setThresholds(std::vector&lt; float &gt; &amp;thres)</div><div class="ttdoc">Specify the thresholds to be used when evaluating features.</div><div class="ttdef"><b>Definition:</b> decision_tree_trainer.h:156</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_html_ad3d53bab672146cea68fd91e86a169fc"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer.html#ad3d53bab672146cea68fd91e86a169fc">pcl::DecisionTreeTrainer::thresholds_</a></div><div class="ttdeci">std::vector&lt; float &gt; thresholds_</div><div class="ttdoc">Thresholds to be used instead of generating uniform distributed thresholds.</div><div class="ttdef"><b>Definition:</b> decision_tree_trainer.h:235</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_html_add4301c8ebb4704365ca7e6c5293a7ff"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer.html#add4301c8ebb4704365ca7e6c5293a7ff">pcl::DecisionTreeTrainer::setLabelData</a></div><div class="ttdeci">void setLabelData(std::vector&lt; LabelType &gt; &amp;label_data)</div><div class="ttdoc">Sets the label data corresponding to the example data.</div><div class="ttdef"><b>Definition:</b> decision_tree_trainer.h:138</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_html_adfa12496668f181e8128e657fdb0bb01"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer.html#adfa12496668f181e8128e657fdb0bb01">pcl::DecisionTreeTrainer::setExamples</a></div><div class="ttdeci">void setExamples(std::vector&lt; ExampleIndex &gt; &amp;examples)</div><div class="ttdoc">Example indices that specify the data used for training.</div><div class="ttdef"><b>Definition:</b> decision_tree_trainer.h:129</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_html_ae52d59ebb69707299a041792b22f6c27"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer.html#ae52d59ebb69707299a041792b22f6c27">pcl::DecisionTreeTrainer::max_tree_depth_</a></div><div class="ttdeci">size_t max_tree_depth_</div><div class="ttdoc">Maximum depth of the learned tree.</div><div class="ttdef"><b>Definition:</b> decision_tree_trainer.h:214</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_html_ae827187aa26efc229653ef2eda9153b4"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer.html#ae827187aa26efc229653ef2eda9153b4">pcl::DecisionTreeTrainer::setMinExamplesForSplit</a></div><div class="ttdeci">void setMinExamplesForSplit(size_t n)</div><div class="ttdoc">Sets the minimum number of examples to continue growing a tree.</div><div class="ttdef"><b>Definition:</b> decision_tree_trainer.h:147</div></div>
<div class="ttc" id="aclasspcl_1_1_decision_tree_trainer_html_afca25306578c18cc5e6891d1fde37370"><div class="ttname"><a href="classpcl_1_1_decision_tree_trainer.html#afca25306578c18cc5e6891d1fde37370">pcl::DecisionTreeTrainer::feature_handler_</a></div><div class="ttdeci">pcl::FeatureHandler&lt; FeatureType, DataSet, ExampleIndex &gt; * feature_handler_</div><div class="ttdoc">FeatureHandler instance, responsible for creating and evaluating features.</div><div class="ttdef"><b>Definition:</b> decision_tree_trainer.h:221</div></div>
<div class="ttc" id="aclasspcl_1_1_feature_handler_html"><div class="ttname"><a href="classpcl_1_1_feature_handler.html">pcl::FeatureHandler</a></div><div class="ttdoc">Utility class interface which is used for creating and evaluating features.</div><div class="ttdef"><b>Definition:</b> feature_handler.h:55</div></div>
<div class="ttc" id="aclasspcl_1_1_stats_estimator_html"><div class="ttname"><a href="classpcl_1_1_stats_estimator.html">pcl::StatsEstimator&lt; LabelType, NodeType, DataSet, ExampleIndex &gt;</a></div></div>
<div class="ttc" id="acommon_2include_2pcl_2common_2common_8h_html"><div class="ttname"><a href="common_2include_2pcl_2common_2common_8h.html">common.h</a></div></div>
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